com.numericalmethod.suanshu.stats.stochasticprocess.univariate.sde
Class Ft

java.lang.Object
  com.numericalmethod.suanshu.stats.stochasticprocess.univariate.sde.Ft

All Implemented Interfaces:

DeepCopyable

Direct Known Subclasses:

FtWt

public class Ft
extends java.lang.Object
implements DeepCopyable

This represents the concept 'Filtration', the information available at time t.

The information can include, for example,

• time
• value of the stochastic process
• values of the driving Brownian motion(s)

See Also:

"Fima C. Klebaner. Introduction to Stochastic Calculus with Applications. 2nd ed. pp.23. Imperial College Press. 2006."

Constructor Summary

Ft()
Construct an empty filtration (no information).

Ft(Ft that)
Copy constructor.

Method Summary

Ft	deepCopy() The implementation can return an instance created from this by the copy constructor of the class, or just this if the instance itself is immutable.
double	dt() Get the current time differential.
double	dWt() Get the increment of the driving Brownian motion during the time differential.
void	setDt(double dt) Set the current time differential.
void	setXt(double Xt) Set the current value of the stochastic process.
void	setZt(double Zt) Set the value of the Gaussian distribution innovation.
double	Xt() Get the current value of the stochastic process.
double	Zt() Get the current value of the Gaussian distribution innovation.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Ft

public Ft()

Construct an empty filtration (no information).

Ft

public Ft(Ft that)

Copy constructor.

Parameters:

that - another Ft

Method Detail

deepCopy

public Ft deepCopy()

Description copied from interface: DeepCopyable

The implementation can return an instance created from this by the copy constructor of the class, or just this if the instance itself is immutable.

Specified by:

deepCopy in interface DeepCopyable

Returns:

an independent (deep) copy of the instance

setDt

public void setDt(double dt)

Set the current time differential.

Parameters:

dt - the time differential

dt

public double dt()

Get the current time differential.

Returns:

the time differential

setXt

public void setXt(double Xt)

Set the current value of the stochastic process.

Parameters:

Xt - the current value of the stochastic process

Xt

public double Xt()

Get the current value of the stochastic process.

Returns:

the current value of the stochastic process

setZt

public void setZt(double Zt)

Set the value of the Gaussian distribution innovation.

Parameters:

Zt - the Gaussian distribution innovation

Zt

public double Zt()

Get the current value of the Gaussian distribution innovation.

Returns:

the current Gaussian distribution innovation

dWt

public double dWt()

Get the increment of the driving Brownian motion during the time differential.

This is the product of the Gaussian distribution innovation and the square root of the time differential.

Returns:

the increment of the driving Brownian motion during the time differential